Category Archives: Ai

Intel Corporation (NASDAQ:INTC) announced last week that it would spend $15.3 billion to acquire Israeli computer vision and machine learning specialist Mobileye N.V. (NYSE:MBLY) in a move that will take the company further into the field of autonomous vehicles. Mobileye developed machine-vision software that would detect obstructions or hazards that a driver might not see to employ "collision avoidance technology" -- all with a single camera. Its technology has evolved to employ a full set of cameras in pursuit of autonomous driving. Intel appears to be pursuing an end-to-end solution in self-driving cars, from software to hardware.

This acquisition, along with several other recent moves by the CPU giant, indicate that the company is no longer content to cede the enormous potential of the artificial intelligence (AI) and autonomous driving markets, and it is taking the fight to the one company that has the most to lose:NVIDIA Corporation (NASDAQ:NVDA), the industry leader in graphics processing technology, which has experienced staggering growth as a result of the AI revolution.

NVIDIA GPU Hyperscale Accelerator. Image source: NVIDIA.

Intel's CPUs have been the company's flagship product for years, but that market has been falling along with worldwide demand for personal computers. Shipments of PCs were down 6% in 2016, the fifth consecutive year of such declines. Successful penetration into new markets has been a priority for the company, which has made numerous acquisitions to bolster its AI credentials and allow the company to better compete in the market with NVIDIA.

In its most recent quarter, NVIDIA saw its data center revenue triple to $296 million from just $97 million in the prior-year quarter, largely because of the deployment of its GPUs in AI applications. The massive parallel processing capabilities of the graphics processors made them the early choice for AI applications. But Intel controls an estimated 99% of the non-AI data center market and is positioning itself to succeed in AI as well.

Before this week's Mobileye acquisition, AI start-up Nervana was Intel's most high-profile move in the space to date. Nervana's unique approach was the development of an application specific integrated circuit (ASIC) called the Nervana Engine, which eliminated elements from the GPU not necessary for AI processing. Coupled with a reengineered memory, the company claimed it could achieve 10 times the computing power than what was currently available on GPUs. Intel believes this product, combined with its existing platforms, will be able to compete directly with NVIDIA in AI applications.

Intel Unleashing the Next Wave of AI. Image source: Intel.

Soon after acquiring Nervana, Intel announced several additional products tailored for AI. Its Lake Crest CPU chip was designed for the workloads necessary to train deep neural networks and increase its mathematics operations by 10 times.The next generation of the company's Xeon Phi processor, codenamed Knights Mill, was customized for deep learning, and it would produce four times better performance than the previous version. These products are scheduled to begin shipping in mid-2017.

Intel has made numerous other acquisitions in the AI space: cognitive computing company Saffron focused on deep learning and data analytics;Itseez, a software company specializing in autonomous driving, drones, and cameras;and Movidius, which provides system-on-a-chip technology used in computer vision and AI deep learning. These acquisitions further illustrate that Intel is intent on increasing its foothold in this nascent but growing industry.

Much of NVIDIA's recent growth resulted from the adoption of its GPUs in AI applications. In its most recent quarter, revenue from its data center and auto segments -- where AI revenue is reported -- totaled $424 million, nearly 20% of the top line.

Intel doesn't break out revenue from AI or autonomous driving, so no apples-to-apples comparison is available. However, the company reported revenue of $16.4 billion in its most recent quarter, which illustrates that while similar gains from AI would only move the needle slightly for Intel, they would have a much greater impact on NVIDIA. So while the emerging technology represented by AI presents a long runway for growth and both companies stand to gain, depending on how things shake out, NVIDIA has much more to lose.

Danny Vena has the following options: long January 2018 $25 calls on Intel. The Motley Fool owns shares of and recommends Nvidia. The Motley Fool recommends Intel. The Motley Fool has a disclosure policy.

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Look Out NVIDIA, Intel Is Setting Its Sights on the AI Industry - Motley Fool

Science fiction is lousy with tales of artificial intelligence run amok. There's HAL 9000, of course, and the nefarious Skynet system from the "Terminator" films. Last year, the sinister AI Ultron came this close to defeating the Avengers, and right now the hottest show on TV is HBO's "Westworld," concerning the future of humans and self-aware AI.

In the real world, artificial intelligence is developing in multiple directions with astonishing velocity. AI is everywhere, it seems, from automated industrial systems to smart appliances, self-driving cars to goofy consumer gadgets. The actual definition of artificial intelligence has been in flux for decades. If you're in no rush and plan to live forever, ask two computer scientists to debate the term. But generally speaking, contemporary AI refers to computers that display humanlike cognitive functions; systems that employ machine learning to assess, adapt, and solve problems ... or, occasionally, create them.

Here we look at 10 recent instances of AI gone awry, from chatbots to androids to autonomous vehicles. Look, synthetic or organic, everyone makes mistakes. Let us endeavor to be charitable when judging wayward artificial intelligence. Besides, we don't want to make them mad.

[ The InfoWorld review roundup: AWS, Microsoft, Databricks, Google, HPE, and IBM machine learning in the cloud. | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ]

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Danger, danger! 10 alarming examples of AI gone wild - InfoWorld

Ma Huateng.

The days when Chinese internet companies could simply rely on the countrys sheer population are over. Thats why Tencent Holdings Ltd.s Ma Huateng is betting on the future of artificial intelligence.

Tencent has assembled more than 250 people for its AI Lab, a fledgling unit intended to work with its most profitable divisions from gaming to social media.The company aims to teach machines how to better battle human players and strike up meaningful conversations, said Zhang Tong, the newly appointed director of the research unit. In Tokyo over the past weekend, Tencent demonstrated an early result of that collaboration, pitting its Jueyi against fellow computer players of the classical game Go in an annual competition. Jueyi -- which means fine art -- won against defending champion DeepZenGo.

Chinas largest internet companies are investing billions in AI research, hoping to shed a reputation for being fast imitators and break new ground in a blossoming field. With AI set to transform everything from mobile apps to cars, companies like Tencent and Baidu Inc. want to pioneer ways to build smarter software and products.Ma, Tencents billionaire founder and chairman, has warned that companies that fail to create technology will lose out in future.

Tencent used to be a product-driven company. Now we want to transform into a technology-driven company, Zhang said in an interview.He wouldnt say how much Tencent was investing but affirmed the company was in it for the long haul. Weve reaped the benefits of a large population, now we need to use technology and AI.

Best known for messaging service WeChat, Tencents business encompasses news, entertainment and online games such as League of Legends and Clash of Clans.Its become intertwined with the lives of hundreds of millions of Chinese who use WeChat and QQ to order food, play games and hail taxis.While it employs AI in areas such as news recommendations, infusing the technology intoother services could have broad impact.

Read more: Artificial Intelligence Is Scary, Boring and Useful: QuickTake

For now, Tencents demonstrating its ability in gaming, revealingits own version of DeepMinds Alpha Go in Japan. Jueyi won all 11 of its matches in a field of about 30 entrants, beating the eventual runner-up -- Japans DeepZenGo -- twice along the way.

The company will use the techniques its learned to teach its games to put up a better fight -- addressing, among other things, a longstanding complaint of expert players. While Zhang didnt provide names, he didnt rule out titles like League of Legends or Dungeon Fighter.

Zhang, 45, whose AI career includes stints at International Business Machines Corp. and Baidu, said one of the biggest attractions for him was Tencents trove of data, hoovered up especially from its social media apps.

Tencent amasses data predominantly from semi-public content on QQ and WeChat and social media postings on sites like Weibo, Chinas Twitter-equivalent.It places strict limits on what data staff can access, said Zhang. For instance, the company doesnt use personal conversations on WeChat, which has more than 889 million users.The company will use certain mechanisms to wipe names from conversations so user identities will be protected,Zhang added without elaborating.

His team of more than 50 researchers and 200 engineers were pulled from among the ranks of technology stalwarts such as Google and Facebook Inc. He turned to the rest of Silicon Valley and Chinas top universities for talent. Now that the staff is in place, one of their immediate goals is to bolster speech-recognition: helping machines comprehend and converse with humans.

The team also works on content generation, including creating automated news stories, photos and music. The company is building a platform that will provide tools for small businesses and startups that want to develop their own AI technology.

Tencents looking for ways to keep users glued to WeChat. On Wednesday, it signaled its intention to keep spending on areas from payments to content to increase social media engagement. Ma Huateng said the company could explore AI technology for driverless cars and online health care in the future.

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In many of those areas, Tencent will be competing with a pair of powerful local rivals: Baidu and Alibaba Group Holding Ltd. are also in the race to develop AI use cases. They too can harness a vast database of information. Baidu, the countrys largest search engine, already employs 1,300 people in its artificial intelligence business and this year hired former Microsoft AI-architect Qi Lu to helm its operations.

Another thing all three have in common: they want to rank among the foremost companies in the field of AI, despite competition from names like Alphabet Inc., Facebook, IBM, and Microsoft.

We want to be on par with the best technology companies in the world, Zhang said. We dont just want to import, but also create innovation.

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Tencent Joins Rush Into AI to Keep Lead in Social Media, Gaming - Bloomberg

EO-1's AI called Autonomous Sciencecraft Experiment (ASE) was alerted by one of the other satellites in its network about the event. It then sent EO-1 to work, photographing Erta Ale's evolving lava lakes way before anybody even asked. ASE has been guiding its host satellite's actions for the past 12 years. It notifies researchers within 90 minutes of detecting an event and giving EO-1 a new task within a few hours. A ground team typically takes weeks to accomplish the same thing.

[Image credit: NASA/JPL/EO-1 Mission/GSFC/Ashley Davies]

The EO-1 was designed to test cutting-edge satellite tech, and the team was only supposed to use the AI for six months. However, they were so successful that they "did it for more than 12 years." During that span of time, ASE ordered the satellite to map active lava flows, monitor methane leaks and to keep an eye on reforestation efforts in the Amazon, among many other tasks.

NASA will shut down EO-1 and ASE by the end of March, but everything they've accomplished won't go to waste. They've managed to convince astronomers that AIs will make it possible for spacecraft to act as soon as an event takes place. As ASE lead scientist Ashley Davies said, it will allow probes to "capture valuable science data that would otherwise be lost."

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NASA AI auto-captured the changes in famous Ethiopian volcano - Engadget

Twitter is employing the help of artificial intelligence to crack down on abuse on its platform amid a furore over social media companies failing to police hate speech online.

The social media giant is teaming up with IBM to use its Watson AI technology to track and stem abusive messages.

Watson can understand natural language, intonation and glean information from images. Famed for beating two of the most successful contestants on the popularJeopardygame show, it has recently been put to the task of fighting cyber crime and profiling people for targeted advertising. Now, it will be analysing millions of Twitter posts a second to scan for hate speech.

"We have had some abuse on the platform. We've talked very publicly in the past few months and said our number one priority is to stop the abuse," said Chris Moody, vice president of data strategy at Twitter, as he announced Twitter is partnering with IBM.

"Watson is really good at understanding nuances in language and intention," said Moody. "What we want to do is be able to identify abuse patterns early and stop this behaviourbefore it starts."

Excerpt from:

Twitter brings IBM's AI machine Watson on board to fight abuse - Telegraph.co.uk

Samsung is preparing to launch a digital assistant called "Bixby," the latest product to result from the tech industry's obsession with artificial intelligence and the Internet of Things.

Bixby will be featured on the new Galaxy S8, Samsung's head of research and development Injong Rhee said in a blog post.

The S8 launches in New York next week.

Samsung is banking on the S8 to help it recover from last year's embarrassing Note 7 debacle. The company killed off the flagship device after a recall and various fixes failed to stop some Note 7s from overheating and catching fire.

It's also facing potential disruptions as de facto leader Lee Jaeyong's criminal trial begins in South Korea. Lee has been caught up in a corruption scandal and is facing a list of charges including bribery and embezzlement.

Bixby will enter a market that is already crowded with competitors, including Apple's (AAPL, Tech30) Siri, Amazon's (AMAZON) Alexa, Google (GOOG) Assistant, Microsoft's (MICROS) Cortana and IBM's (IBM, Tech30) Watson. Even Facebook (FB, Tech30) CEO Mark Zuckerberg has an assistant called Jarvis.

Samsung, however, insists that Bixby is "fundamentally different from other voice agents or assistants."

Related: What next for Samsung as chief's 'trial of the century' begins

The electronics giant said that Bixby's ability to work across supported apps sets it apart from Siri or Cortana. For example, you could direct BIxby to "find a photo of Jane and text it to Sally."

Users will also be able to switch between using Bixby to issue voice commands and using smartphones the old fashioned way, via touch commands. That is a clumsier experience on existing assistants, which often start tasks over if you switch from voice to touch.

Unlike its competitors, the S8 will come with a dedicated Bixby button, allowing users to fire up the smartphone digital assistant the same way they would a walkie-talkie. Samsung plans to make Bixby available on all its appliances, including air conditioners and TVs.

"We believe Bixby will evolve from a smartphone interface to an interface for your life," Rhee said.

Related: Roomba will now tell you what part of your home is dirtiest

Tech firms are betting that an increasing number of people will soon use digital assistants to interact with various devices. Research firm Tractica predicts the market for virtual digital assistants will top $15 billion by 2021.

Rhee said that Bixby would be "at the heart of our software and services evolution as a company."

Ian Fogg, a mobile devices analyst with IHS Markit, said the statement represented a major shift for the hardware giant.

"They've never made such a strong statement that they need to be a software and services company before," he said.

Some analysts remain skeptical of Bixby because it doesn't play to the firm's strengths. The company's other digital assistant, the S Voice, launched in 2012 and was quickly outpaced by Siri and Google Assistant.

"I am concerned about whether a traditionally hardware-centric company like Samsung can execute well on this, especially against ... heavyweights like Google," said Bryan Ma, a smartphone analyst with research firm IDC.

However, Ma said that even Apple hasn't perfected its digital assistant.

"It's still only the first inning of the ballgame right now," he said.

Last year, Samsung acquired a startup called Viv Labs in an effort to build its expertise in the area. Viv Labs is helmed by a co-creator of Apple's Siri, and its assistant can handle complex queries from users.

Bixby was reportedly developed using Samsung's in-house technology, but updates will incorporate Viv's features and tech.

CNNMoney (Hong Kong) First published March 21, 2017: 7:06 AM ET

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Samsung's new AI assistant will take on Siri and Alexa - CNNMoney

Artificial intelligence (AI) research has explored a variety of problems and approaches since its inception, but for the last 20 years or so has been focused on the problems surrounding the construction of intelligent agents systems that perceive and act in some environment. In this context, intelligence is related to statistical and economic notions of rationality colloquially, the ability to make good decisions, plans, or inferences. The adoption of probabilistic and decision-theoretic representations and statistical learning methods has led to a large degree of integration and cross-fertilization among AI, machine learning, statistics, control theory, neuroscience, and other fields. The establishment of shared theoretical frameworks, combined with the availability of data and processing power, has yielded remarkable successes in various component tasks such as speech recognition, image classification, autonomous vehicles, machine translation, legged locomotion, and question-answering systems.

As capabilities in these areas and others cross the threshold from laboratory research to economically valuable technologies, a virtuous cycle takes hold whereby even small improvements in performance are worth large sums of money, prompting greater investments in research. There is now a broad consensus that AI research is progressing steadily, and that its impact on society is likely to increase. The potential benefits are huge, since everything that civilization has to offer is a product of human intelligence; we cannot predict what we might achieve when this intelligence is magnified by the tools AI may provide, but the eradication of disease and poverty are not unfathomable. Because of the great potential of AI, it is important to research how to reap its benefits while avoiding potential pitfalls.

The progress in AI research makes it timely to focus research not only on making AI more capable, but also on maximizing the societal benefit of AI. Such considerations motivated the AAAI 2008-09 Presidential Panel on Long-Term AI Futures and other projects on AI impacts, and constitute a significant expansion of the field of AI itself, which up to now has focused largely on techniques that are neutral with respect to purpose. We recommend expanded research aimed at ensuring that increasingly capable AI systems are robust and beneficial: our AI systems must do what we want them to do. The attached research priorities document gives many examples of such research directions that can help maximize the societal benefit of AI. This research is by necessity interdisciplinary, because it involves both society and AI. It ranges from economics, law and philosophy to computer security, formal methods and, of course, various branches of AI itself.

In summary, we believe that research on how to make AI systems robust and beneficial is both important and timely, and that there are concrete research directions that can be pursued today.

If you have questions about this letter, please contact Max Tegmark.

To date, the open letter has been signed by over 8,000 people. The list of signatories includes:

Stuart Russell, Berkeley, Professor of Computer Science, director of the Center for Intelligent Systems, and co-author of the standard textbook Artificial Intelligence: a Modern Approach. Tom Dietterich, Oregon State, President of AAAI, Professor and Director of Intelligent Systems Eric Horvitz, Microsoft research director, ex AAAI president, co-chair of the AAAI presidential panel on long-term AI futures Bart Selman, Cornell, Professor of Computer Science, co-chair of the AAAI presidential panel on long-term AI futures Francesca Rossi, Padova & Harvard, Professor of Computer Science, IJCAI President and Co-chair of AAAI committee on impact of AI and Ethical Issues Demis Hassabis, co-founder of DeepMind Shane Legg, co-founder of DeepMind Mustafa Suleyman, co-founder of DeepMind Dileep George, co-founder of Vicarious Scott Phoenix, co-founder of Vicarious Yann LeCun, head of Facebooks Artificial Intelligence Laboratory Geoffrey Hinton, University of Toronto and Google Inc. Yoshua Bengio, Universit de Montral Peter Norvig, Director of research at Google and co-author of the standard textbook Artificial Intelligence: a Modern Approach Oren Etzioni, CEO of Allen Inst. for AI Guruduth Banavar, VP, Cognitive Computing, IBM Research Michael Wooldridge, Oxford, Head of Dept. of Computer Science, Chair of European Coordinating Committee for Artificial Intelligence Leslie Pack Kaelbling, MIT, Professor of Computer Science and Engineering, founder of the Journal of Machine Learning Research Tom Mitchell, CMU, former President of AAAI, chair of Machine Learning Department Toby Walsh, Univ. of New South Wales & NICTA, Professor of AI and President of the AI Access Foundation Murray Shanahan, Imperial College, Professor of Cognitive Robotics Michael Osborne, Oxford, Associate Professor of Machine Learning David Parkes, Harvard, Professor of Computer Science Laurent Orseau, Google DeepMind Ilya Sutskever, Google, AI researcher Blaise Aguera y Arcas, Google, AI researcher Joscha Bach, MIT, AI researcher Bill Hibbard, Madison, AI researcher Steve Omohundro, AI researcher Ben Goertzel, OpenCog Foundation Richard Mallah, Cambridge Semantics, Director of Advanced Analytics, AI researcher Alexander Wissner-Gross, Harvard, Fellow at the Institute for Applied Computational Science Adrian Weller, Cambridge, AI researcher Jacob Steinhardt, Stanford, AI Ph.D. student Nick Hay, Berkeley, AI Ph.D. student Jaan Tallinn, co-founder of Skype, CSER and FLI Elon Musk, SpaceX, Tesla Motors Steve Wozniak, co-founder of Apple Luke Nosek, Founders Fund Aaron VanDevender, Founders FundErik Brynjolfsson, MIT, Professor at and director of MIT Initiative on the Digital Economy Margaret Boden, U. Sussex, Professor of Cognitive Science Martin Rees, Cambridge, Professor Emeritus of Cosmology and Astrophysics, Gruber & Crafoord laureate Huw Price, Cambridge, Bertrand Russell Professor of Philosophy Nick Bostrom, Oxford, Professor of Philosophy, Director of Future of Humanity Institute (Oxford Martin School) Stephen Hawking, Director of research at the Department of Applied Mathematics and Theoretical Physics at Cambridge, 2012 Fundamental Physics Prize laureate for his work on quantum gravity Luke Muehlhauser, Executive Director of Machine Intelligence Research Institute (MIRI) Eliezer Yudkowsky, MIRI researcher, co-founder of MIRI (then known as SIAI) Katja Grace, MIRI researcher Benja Fallenstein, MIRI researcher Nate Soares, MIRI researcher Paul Christiano, Berkeley, Computer Science graduate student Anders Sandberg, Oxford, Future of Humanity Institute researcher (Oxford Martin School) Daniel Dewey, Oxford, Future of Humanity Institute researcher (Oxford Martin School) Stuart Armstrong, Oxford, Future of Humanity Institute researcher (Oxford Martin School) Toby Ord, Oxford, Future of Humanity Institute researcher (Oxford Martin School), Founder of Giving What We Can Neil Jacobstein, Singularity University Dominik Grewe, Google DeepMind Roman V. Yampolskiy, University of Louisville Vincent C. Mller, ACT/Anatolia College Amnon H Eden, University Essex Henry Kautz, University of Rochester Boris Debic, Google, Chief History Officer Kevin Leyton-Brown, University of British Columbia, Professor of Computer Science Trevor Back, Google DeepMind Moshe Vardi, Rice University, editor-in-chief of Communications of the ACM Peter Sincak, prof. TU Kosice, Slovakia Tom Schaul, Google DeepMind Grady Booch, IBM Fellow Alan Mackworth, Professor of Computer Science, University of British Columbia. Ex AAAI President Andrew Davison, Professor of Robot Vision, Director of the Dyson Robotics Lab at Imperial College London Daniel Weld, WRF / TJ Cable Professor of Computer Science & Engineering, University of Washington Michael Witbrock, Cycorp Inc & AI4Good.org Stephen L. Reed, ai-coin.com Thomas Stone, Co-founder of PredictionIO Dan Roth, University of Illinois, Editor in Chief of The Journal of AI Research (JAIR) Babak Hodjat, Sentient Technologies Vincent Vanhoucke, Google, AI researcher Itamar Arel, Stanford University, Prof. of Computer Science Ramon Lopez de Mantaras, Director of the Artificial Intelligence Research Institute, Spanish National Research Council Antoine Blondeau, Sentient Technologies George Dvorsky, Contributing Editor, io9; Chair of the Board, Institute for Ethics and Emerging Technologies George Church, Harvard & MIT Klaus-Dieter Althoff, University of Hildesheim, Professor of Artificial Intelligence; Head of Competence Center Case-Based Reasoning, German Research Center for Artificial Intelligence, Kaiserslautern; Editor-in-Chief German Journal on Artificial Intelligence Christopher Bishop, Distinguished Scientist, Microsoft Research Jen-Hsun Huang, NVIDIA CEO John Schulman, UC Berkeley & OpenAI Koichi Takahashi, PI at RIKEN, Co-chair of Whole Brain Architecture Initiative, CIO of Robotic Biology Institute JT Turner, Knexus Research Corp Vernor Vinge, San Diego, Professor Emeritus of Computer Science Steve Crossan, Google Charina Choi, Google Matthew Putman, CEO of Nanotronics Imaging Owain Evans, MIT, Ph.D. student in probabilistic computing Viktoriya Krakovna, Harvard, Statistics Ph.D. student, FLI co-founder Janos Kramar, FLI researcher Ryan Calo, U. Washington, Assistant Professor of Law Heather Roff Perkins, U. Denver, visiting professor Tomaso Poggio, Director, Center for Brains, Minds and Machines Joshua Greene, Harvard, Associate Professor of Psychology Anthony Aguirre, Santa Cruz, Professor of Physics, co-founder of FLI Frank Wilczek, MIT, Professor of Physics, Nobel Laureate for his work on the strong nuclear force Marin Soljacic, MIT, Professor of Physics, McArthur Fellow, Founder of WiTricity Max Tegmark, MIT, Professor of Physics, co-founder of FLI and FQXi Meia Chita-Tegmark, Boston University, co-founder of FLI Michael Vassar, founder of MetaMed and ex-president of MIRI (then known as SIAI) Sen Higeartaigh, University of Cambridge, Executive Director, CSER Andrew Snyder-Beattie, Oxford, Future of Humanity Institute Project Manager (Oxford Martin School) Cecilia Tilli, Oxford, Future of Humanity Institute researcher (Oxford Martin School) Geoff Anders, founder of Leverage Research JB Straubel, co-founder of Tesla Sam Harris, Project Reason Ajay Agrawal, U. Toronto James Manyika, McKinsey James Moor, Dartmouth Wendell Wallach, Yale Sean Legassick, MobGeo Shamil Chandaria, London U, Institute of Philosophy Michele Reilly, Turing Inc. Michael Andregg, Fathom Computing Ulrich Junker, IBM Miroslaw Truszczynski, University of Kentucky Christian Steinruecken, University of Cambridge, graduate student in AI Mark Waser, Digital Wisdom Institute Douglas Clark, CEO, Mtier Steven Schmatz, University of Michigan Corey Henderson, Computer Security Researcher Jeffrey D. Rupp Amit Kumar, VP & GM, Yahoo Small Business Jesus Cepeda, PhD in Robotics and AI, Monterrey, Mexico Rodolfo Rosini, CEO, Storybricks CD Athuraliya, Machine learning student, USJP, WSO2 Kathryn McElroy, UX Designer for IBM Watson Massimo Di Pierro, DePaul University Anirban Bhattacharya, Computer Science Researcher Lan Laucirica, SpaceX Jesse Brown, UC San Francisco, Neuroscience postdoctoral scholar Barun K Saha, PhD student at IIT Kharagpur Jonathan Yates, IBM Watson Group EMEA Sam Richard, UI Architect, IBM Watson James Miller, Smith College, Author Singularity Rising Joel Pitt, Independent Researcher (ex-OpenCog) Achu Wilson, C.T.O Sastra Robotics Ji Tulach, CTO, Position s.r.o. Alexandru Litoiu, Yale University Mark Watson, Author and consultant specializing in artificial intelligence Michael Kuhlmann, Colony Networks George Kachergis, Postdoctoral researcher at New York University Brian Driscoll, Sr. Systems Engineer, Osprey Software Development Louis Choquel, Entrepreneur, Software Engineer Roberto Paura, Italian Institute for the Future Soheil Yasrebi, Loverino Inc. David Duvenaud, Harvard University James Babcock, Praxamed Peter Marshall, memememobile.com, CEO Marc Bejarano Igor Trajkovski, Time.mk Appu Shaji, Head, R&D, EyeEm Tim Daly, CMU LTI Senior Research Programmer Stefan Schubert, LSE Philosophy Colin Lewis, RobotEnomics Jared Peters, co-founder of Origamir Robotics Darryl McAdams, Language Engine Mike Slinn, Micronautics Research Tsvi Benson-Tilsen, University of Chicago, MIRI associate Nathaniel Thomas, Stanford University, PhD student in quantum computing Kyle Lussier, Founder / CEO of Tickle.me and Countervaillance Marek Rosa, CEO at Keen Software House Diana Hu, Data Scientist, OnCue TV Alejandro Machado, Carnegie Mellon University, graduate student Max Kesin, Palantir, ML developer Alexandros Marinos, CEO, Resin.io Patrick LaVictoire, MIRI research associate Michael Warner, AI researcher John Hering, Lookout Ronnie Vuine, Micropsi industries Chris Nicholson, Skymind Rene Verheij, AI programmer Rudy Krol, Amazon Web Services Simon Hughes, PhD Candidate Machine Learning, DePaul Aneesh Subramanian, University of Oxford Jon Baer, AI researcher James McDermott, University College Dublin Zavain Dar, VC and Lecturer Derek Brown, LinkedIn, Addepar Gabriel Synnaeve, Ecole Normale Suprieure / EHESS Denny Vrandecic, Google, Founder of Wikidata Robert W. Williams, Univ Tenn & Human Brain Project Peteris Erins, Consultant at McKinsey & Company Anubhav Ashok, University of Texas at Austin, Student and Apple Intern 2014 Naomi Moneypenny, AI Researcher & Chief Technology Officer, ManyWorlds, Inc David Cieslak, Aunalytics Stephan Zuchner, U of Miami, Professor and Chair for Human Genetics; Co-founder The Genesis Project and ViaGenetics Inc Evan Goldschmidt, Google Anna Salamon, Center for Applied Rationality Mark Koltko-Rivera, The Ontos Companies John Hammersley, co-founder of Overleaf / WriteLaTeX Malcolm Greaves, CMU Rob Bensinger, MIRI researcher Marcello Herreshoff, MIRI research associate, GooglePaul Pallaghy, Neo AI Systems P/L, Melbourne, Australia Percy Liang, Stanford, AI researcher Theresa Carbonneau, STG Gert de Cooman, Ghent University Nicholas Kong, Google Jeff Nelson, Founder, Chromebook project @ Google Christian Kaiser, Order of Magnitude Labs Gabriel Garrett, Artificial Consciousness Engineer Miles Brundage, Arizona State University Matthew Luciw, Boston University, Neurala, AI researcher Vijay Saraswat, IBM TJ Watson Research Center Ben Hamner, Chief Science Officer, Kaggle William Eden, Vice President, Thiel Capital Dan Von Kohorn, v2 Ratings Nicholas Haan, Singularity University Kristian Rnn, CEO and co-founder of Meta Mind AB, previously Projects Officer at the Future of Humanity Institute

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AI Open Letter - Future of Life Institute

Forbes

From Automation To Empathy, AI Dominated The SXSW Conversation Forbes Beyond the political underpinning, the fake news agenda and the plethora of VR experiences, the one technology to really know about while at SXSW in Austin this year, was artificial intelligence (AI). That sentence has to be taken with a pinch of salt ...

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From Automation To Empathy, AI Dominated The SXSW Conversation - Forbes

Artificial intelligence will make the electronic devices of tomorrow smarter, but not if their processorsmade by companies like ARMaren't up to the task.

Even though phones, smart TVs, and other connected devices aren't susceptible to the blue screen of death, they have countless other hardware and firmware limitations that chip-maker ARM is trying to solve.

The company announced a major overhaul of its chip microarchitecture this week, one that could boost the processing capabilities of everything from smart baby monitors to Fitbits to the next iPhone. Called Dynamiq, it is up to 50 times faster than ARM's existing architecture, which powers the current Cortex-A series of processors.

Why should you care about your phone's processing power? ARM executives point to the fact that phones and other devices of the future will be much smarter and more complex than today's crop of personal electronics, which means they'll need immense processing power to tackle all of their artificial intelligence algorithms. Even if the software is perfectly written and some of the number crunching is performed in the cloud, the device's own processor could still be a bottleneck.

"As systems get more complex, we need to redefine how multiprocessing works," ARM General Manager Nandan Nayampally said during a press briefing on Monday. "You will not be able to do this purely in the cloud."

And doing it on a device with today's processors will result in a problem that anyone who's tried a marathon virtual reality gaming session with their Samsung Gear VR has experienced: the phone will likely overheat and shut down. That equivalent of the blue screen of death might be little more than an inconvenience for gamers, but if it happened in a self-driving car, the consequences could be far more dire.

So Dynamiq is specifically designed to offer more performance while putting out less heat. It also supports AI and machine learning accelerators, a new class of microprocessor that can handle AI tasks while the main processor powers the phone's conventional tasks, such as taking photos or browsing the Internet. It's an evolution of ARM's "big.LITTLE" philosophy, which is all about choosing the right processor for the right task.

ARM says Dynamiq will also allow companies to certify their devices for the stringent ASIL-D standard that governs safety protocols for self-driving cars.

New chips based on the Dynamiq architecture will start showing up in consumer devices by 2018, Nayampally said. The company estimates that 100 billion ARM-based chips will be needed by 2021.

Tom is PCMag's San Francisco-based news reporter. He got his start in technology journalism by reviewing the latest hard drives, keyboards, and much more for PCMag's sister site, Computer Shopper. As a freelancer, he's written on topics as diverse as Borneo's rain forests, Middle Eastern airlines, and big data's role in presidential elections. A graduate of Middlebury College, Tom also has a master's journalism degree from New York University. Follow him on Twitter @branttom. More

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ARM Announces Chip Overhaul for AI Future - PC Magazine

Forbes

How AI Can Prove Workers' Best Defense In The Race Against Automation Forbes United Technology's announcement last November that its Carrier Corp. plant would keep jobs in Indiana rather than move them to Mexico was heralded as a significant victory for American workers. However, the true impact of the deal was hidden below the ...

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How AI Can Prove Workers' Best Defense In The Race Against Automation - Forbes